Osmotic dehydration of replacement lung surfactant: Implications for ARDS therapy.

The potentially fatal condition of Acute Respiratory Distress Syndrome (ARDS) begins with damage to the lung, which then becomes flooded with fluid rich in serum protein. These serum proteins inactivate the lung surfactant (LS) that lines the alveoli, raising alveolar surface tension and resulting in lung collapse. Previous studies have shown that the addition of nonionic polymers to therapeutic replacement lung surfactant (RLS) restores the surface activity of RLS in the presence of inactivating substances, a possible explanation being the dehydration of RLS vesicles by polymer-induced depletion forces. This study tested the hypothesis that RLS whose surface activity responds to the addition of polymer will also experience dehydration upon application of known osmotic stress. The interlamellar spacing (d) of the porcine extract RLS Curosurf and the synthetic RLS Exosurf was measured using small-angle X-ray scattering in the presence of polymer and/or bovine serum albumin (BSA) at various concentrations. Polymers used were polyethylene glycol (PEG, 10 or 20 kDa) and 150 kDa Dextran. The applied osmotic pressures were 10^0 - 10^8 dynes/cm^2. Over this range of pressures, Curosurf experiences a 50Å change in d that fits an exponential curve with decay constant of 7.22 ± 0.23 Å, similar to the Debye length in 150 mM solution. This may indicate the presence of electrostatic interactions. The Exosurf d lie within a range of 59-72 Å but exhibit no definite trend. These results suggest that added polymer in the concentrations utilized would not improve the surface activity of Exosurf, but that osmotic stress may indeed be a mechanism by which polymers restore the function of inactivated Curosurf. To investigate the effect of PEG on the surface activity of Exosurf, pressure-area isotherms of Exosurf spread from chloroform on 150 mM NaCl, 5 mM CaCl2, 1.5 mM tris-HCl, pH 7.2-7.4, were recorded at 24.5ºC in the presence and absence of 5% PEG (m.w. 10 kDa) and 2 mg/mL BSA. Upon repeated compressions of Exosurf on 5% PEG solution, a decrease in the length of the fluid-condensed phase coexistence region in the isotherm suggested the dissolution of Tyloxapol into the subphase

The Importance of Soft Skills for Academic Performance and Career Development—From the Perspective of University Students

In the present era, the importance of soft skills as a crucial element for personal and professional success is widely acknowledged. When hiring new employees, these soft skills are highly valued by employers. However, many students are unaware of the crucial role those soft skills play in their education and career success, hindering their progress in developing these skills. This study aims to assess students’ perceptions of the importance of soft skills for academic performance and career development. A questionnaire-based online survey was conducted, involving 968 undergraduate students from eight universities in Vietnam, to gather data. The findings showed that most respondents recognized the significance of soft skills in fostering positive relationships, career advancement, and securing desirable employment. However, students did not believe that these skills had a substantial impact on their academic performance. Communication, teamwork, collaboration, and time management skills were identified as the most critical soft skills for enhancing academic performance, while teamwork, collaboration, leadership, and problem-solving skills were considered pivotal for career development. Moreover, a significant portion of students perceived their soft skills level to be below the desired threshold, showing more confidence in skills they considered to be more important. Similarly, students tended to prioritize the development of soft skills that they perceived as essential to their personal goals

Fixed-to-mobile substitution in the US, EU, and China: Forecasting technology diffusion using the Lotka-Volterra Competition model

Objectives The first purpose of this thesis is to test the performance of the Lotka – Volterra Competition model in forecasting demand for technologies. Secondly, the paper aims to determine the interrelationship between the markets and their expected behaviors based on population theories. Thirdly, it attempts to gauge the similarities and differences of market behaviors in the most developed economies based on GDPpc as of October 2018. Summary Total annual subscription for each market was used to perform in-sample forecasts. Parameterization was obtained using the Gauss-Newton non-linear least squares method with the Marquardt algorithm. Then, the stable equilibria were shown in the interactive outcome graphs, which indicate that the theoretical suggestions are well-supported by historical market patterns. Conclusions The results indicate high fitting performance (R-squares>0.98) with estimated data close to that of actual observations. Despite data complications, the model has a good degree of accuracy. The competitive relationships for the US, the EU, and China are suggested to be amensalism, amensalism, and pure competition, respectively. The equilibrium analyses show that in all scenarios, the mobile cellular market dominates the fixed-line phone market. Over time, mobile phones will substitute fixed – line phones and obtain maximum growth

Perception of Engineering Students on Social Constructivist Learning Approach in Classroom

The social constructivist approach to teaching and learning has garnered significant interest among educators and researchers. However, further investigation into its implementation and effectiveness in the classroom is still needed. This study aims to investigate engineering students’ perceptions of social constructivist practices in their technology classes, using the constructivist learning environment survey (CLES) as its framework. A mixed-methods approach combining quantitative and qualitative methods was used, which included online surveys and semi-structured interviews. Analysis of data from 300 responses showed that constructivism was partially implemented in the classroom. Specifically, student negotiation emerged as the most frequently perceived dimension, while shared control was perceived as seldom occurring. Most items on the personal relevance scale were frequently perceived, highlighting the importance of integrating technology learning into students’ daily lives. Similarly, the uncertainty of technology was found to be a common experience for students. In contrast, the dimension of critical voice received mixed results, emphasizing the necessity of a learning environment that fosters student expression and meaningful discussions. These findings suggest the necessity for additional investigation and integration of social constructivist practices that emphasize the enhancement of student engagement, promotion of critical thinking, and redistribution of power within the classroom setting

Instrumentation and robotic image processing using top-down model control

A top-down image processing scheme is described. A three-dimensional model of a robotic working environment, with robot manipulators, workpieces, cameras, and on-the-scene visual enhancements is employed to control and direct the image processing, so that rapid, robust algorithms act in an efficient manner to continually update the model. Only the model parameters are communicated, so that savings in bandwidth are achieved. This image compression by modeling is especially important for control of space telerobotics. The background for this scheme lies in an hypothesis of human vision put forward by the senior author and colleagues almost 20 years ago - the Scanpath Theory. Evidence was obtained that repetitive sequences of saccadic eye movements, the scanpath, acted as the checking phase of visual pattern recognition. Further evidence was obtained that the scanpaths were apparently generated by a cognitive model and not directly by the visual image. This top-down theory of human vision was generalized in some sense to the frame in artificial intelligence. Another source of the concept arose from bioengineering instrumentation for measuring the pupil and eye movements with infrared video cameras and special-purpose hardware

Determinants of Female’s Employment Outcomes in Vietnam

In the context of reducing female labor demand and restructuring female work in integration, determinants of women\u27s employment are studied using data of 2010 VHLSS with 11,085 women aged 15 and older who were working in the Vietnamese labor market. The economic and care needs, values and opportunities of women working are important. At the region-level, economic development and equality will give women opportunities for better work. Women\u27s education and training clearly take a key position. The analysis shows the effect of education and training are strongest and positive for women with employment in the group of Leaders, managers, and administrators; High and Middle-level technicians and professionals”. The finding suggests an effect of household social-economic status on women\u27s employment achievements. Our results stress the importance of education and training as the major road towards women\u27s empowerment in Vietnam

Ontology-Based Case Study Management Towards Bridging Training and Actual Investigation Gaps in Digital Forensics

The training programs in digital forensics have contributed many case study models to guide digital forensic analyses. However, they only account for a small number of real cases and they are usually too abstract while actual cybercrime investigations are more diverse and complex. This gap leads to difficulties in giving immediate and straightforward actions for law enforcement during cybercrime investigations. In this paper, we propose an ontology-based knowledge map model, which is a foundation model for building a case study management system for Digital Forensic Intelligence (DFINT) and Open Source Intelligence (OSINT) in digital forensics. The main idea of this proposed model is to encode specific training cases of cybercrime into knowledge map representations, then the system uses the knowledge from the ontology to provide more information on the context and enrich them to match actual cybercrime scenes. Therefore, this approach can be used to bridge the gap between training case studies and the actual investigation environment. To illustrate our approach, we build a DFOSINT ontology for DFINT and OSINT domain; develop a prototype of the case study management system, and evaluate it in two aspects, ontology validation and case study validation with existing case studies of digital investigations

Effects of cellulose nanofibers on soil water retention and aggregate stability

Innovative solutions that address global challenges such as water scarcity and soil erosion are critical for maintaining sustainable agriculture. Due to their water-absorbing and soil-binding properties, cellulose nanofibers (CNF) can be applied to soil to enhance soil water retention and aggregate stability. In this study, we analyzed the effects of the drying temperature, dosage, irrigation water quality, and soil type on the efficacy of CNFs. Our results revealed that CNF dried at 5 degrees C is more effective at absorbing water than others, and adding 1% CNF enhanced soil water content up to 98%. The CNF samples absorbed water due to their hydrophilic molecular groups and morphological structure, as confirmed by Fourier-transform infrared spectroscopy and scanning electron microscopy. CNF addition increased the soil volumetric water content and prolonged water retention by 22 days in the paddy soil samples, highlighting its potential for drought-prone areas. Furthermore, irrigation water quality, such as pH and cation values, influenced the interactions between CNF and water molecules, suggesting adjustments to the water retention curve. In its hydrated state, CNF promotes colloid flocculation and binds to soil particles, thereby strengthening the bonds crucial for aggregate formation and stability. CNF enhanced macro-aggregate formation by up to 48% and 59% in the masa and paddy soil samples, respectively. Our study emphasizes the potential of CNF for water conservation, soil health, and overall agricultural sustainability

OAK4XAI: Model towards Out-Of-Box eXplainable Artificial Intelligence for Digital Agriculture

Recent machine learning approaches have been effective in Artificial Intelligence (AI) applications. They produce robust results with a high level of accuracy. However, most of these techniques do not provide human-understandable explanations for supporting their results and decisions. They usually act as black boxes, and it is not easy to understand how decisions have been made. Explainable Artificial Intelligence (XAI), which has received much interest recently, tries to provide human-understandable explanations for decision-making and trained AI models. For instance, in digital agriculture, related domains often present peculiar or input features with no link to background knowledge. The application of the data mining process on agricultural data leads to results (knowledge), which are difficult to explain. In this paper, we propose a knowledge map model and an ontology design as an XAI framework (OAK4XAI) to deal with this issue. The framework does not only consider the data analysis part of the process, but it takes into account the semantics aspect of the domain knowledge via an ontology and a knowledge map model, provided as modules of the framework. Many ongoing XAI studies aim to provide accurate and verbalizable accounts for how given feature values contribute to model decisions. The proposed approach, however, focuses on providing consistent information and definitions of concepts, algorithms, and values involved in the data mining models. We built an Agriculture Computing Ontology (AgriComO) to explain the knowledge mined in agriculture. AgriComO has a well-designed structure and includes a wide range of concepts and transformations suitable for agriculture and computing domains.Comment: AI-2022 Forty-second SGAI International Conference on Artificial Intelligenc